Machine Learning Software Engineer Intern Jobs in Newark, NJ

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It's why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It's why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it's why our business strategy centers on making journalism so good that it's worth paying for.
About the Role
Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.
The Machine Learning Platform (MLP) team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models with low-latency and Service Level Agreements (SLAs) guaranteed by the MLP.
We are looking for a Software Engineer, with a focus on MLOps, to join our Machine Learning Platform team to help solve creative challenges around Machine Learning infrastructure for the New York Times.
This role is a hybrid role, based in New York City. You will report to the Engineering Manager of the Machine Learning Platform team.
Responsibilities:

• You will research, develop, and deploy infrastructure for the Machine Learning Platform at scale
• You will build infrastructure to train and test algorithms that provide real-time content recommendations and personalization
• You will enhance ML platform's CI/CD and integration testing capabilities
• You will promote developer productivity by rolling out capabilities that maximize self-sufficiency and minimize the toil in learning those capabilities in building scalable applications with high speed, quality, and performance
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 2+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment
• Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)
• Experience working with Kubernetes, Docker, and CI/CD
• Familiarity with at least one high-level programming language like Python or Go

Preferred Qualifications:

• Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, Drone, Triton, TensorFlow, scikit-learn, DataDog
• Experience building real-world machine learning applications like recommendation systems, bandits, etc.
• Experience engaging with stakeholders to understand pain points, observe patterns, and identify opportunities for improvements

This role may require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.
REQ-019501
#LI-Hybrid
The annual base pay range for this role is between:
$110,000-$130,000 USD
For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.
For roles outside of the U.S., information on benefits will be provided during the interview process.
The New York Times Company is committed to being the world's best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.
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